However, identifying offensive language is not a simple task. Challenges during identification include but are not limited to the fact that surface language features fail to capturing subtle semantic difference, and the shortage of undisputed annotated data [1]}. Most of previous studies focus on distinguishing between offensive and non-offensive language [2]}, [3]},
which is the goal of subtask A in the current shared task. But part of challenge consists of the intertwined nature of such messages having negative connotations and profanity.
[4]} show that it is important to tease these two factors apart.
[1]} first address the issue of distinguishing hate speech from general profanity.
